Files
serverAppConfigs/serverAppConfigs-docs/LLM/halogen-flash-server.md
T
Frank 41ac1f83f6 docs(halogen): record the measured arena model; the 65536 experiment was worth doing
Raising HALOGEN_MAX_TOK to 65536 did not shrink the pool, it OOMed the boot:
the arena alone (37.3 GiB) exceeds the 29.5 GiB device budget, so even the
minimum pool faulted and dmalloc failed at 39.97 GiB. Rolled back to 16384,
which restored the 524288 pool and a clean completion.

The three measured arenas are exactly linear in the flag — 3.80 GiB base plus
8.40 GiB per 16384 tokens, predicting all three to 0.1 GiB. That gives a real
sizing rule instead of guesswork, and it says the deployed 16384 is the
CEILING, not a conservative choice: 29.5 - 1.5 margin - 14.4 pool leaves 13.6
for the arena, i.e. max_tok <= 19,115.

The corner check falls out of the same model: set max_tok back to 32768 and
only 7.4 GiB remains for the pool, ~269k positions, which is precisely the
262144 config this host ran before. The two corners of the feasible box are
the only two points it has ever served.

No functional change — the quadlet edit is comments only; the running service
is already at 16384 from the rollback deploy (258cccb).
2026-09-12 19:38:13 -07:00

17 KiB
Raw Blame History


type: reference title: halogen-flash-server on Dankclaw (frank-large) description: The active frank-large runbook — peonist-ai/halogen-flash-server 0.5.8 serving Qwen3.8-Flash-Next (w4b) on the Dankclaw gfx1151 box: container shape, deployed flags, the memory model, the client contract, and the failure modes worth knowing. tags:

  • llm
  • halogen
  • dankclaw
  • frank-large
  • strix-halo
  • gfx1151
  • qwen4exp
  • rocm timestamp: 2026-09-12

halogen-flash-server on Dankclaw (frank-large)

ACTIVE since 2026-09-11. Replaced the llama.cpp / kingjones30-ROCmFPX STRIX deployment (see kingjones-strix-rocmfp4, now the rollback target). Deployed as a rootless Quadlet container, dankclaw/frank-large/quadlet/frank-large.container, port 7770.

The engine is a from-scratch serving runtime for the Qwen3.8-Flash-Next architecture on AMD's gfx1151 (Strix Halo) — the same silicon this host runs. Upstream's own comparison table measures it at roughly 4x the prefill throughput of the llama.cpp-family runtimes it ships against (EngramHalo.cpp, ROCmFP4, CIRU-IU4) on a 32K prompt, and prefill is most of the wall clock on any prompt with real context. That, not decode, is the reason for the swap.

Shape

One container runs both halves of the stack:

half port reachable
engine 8730 container loopback only — unauthenticated, never publish it
OpenAI front-end 8731 published as host 7770

The all mode is upstream's default and the shape a single-container host wants: the front-end talks to the engine over loopback inside the container, so there is one process tree, one log, and one published port.

HALOGEN_MODEL_ID=frank-large sets the id reported at /v1/models, in /health, and in every response body. Requests are never rejected for naming a different model — the server serves whatever asks. Keeping the fleet alias is therefore free, and it means Hermes, the harness config, the OpenWebUI discovery, the services.json probe and the docs needed no rename.

Weights

peonist-ai/halogen-qwen3.8-flash-next (HuggingFace, public and ungated):

file size role
qwen38-flash-next-w4b.hgn 115.55 GiB the checkpoint
qwen38-flash-next-w4b.overlay.hgn 2.31 GiB quality sidecar — picked up automatically; the engine warns at startup if it is missing
qwen38-flash-next-vision.hgn 0.84 GiB vision tower (see below)
tokenizer/ ~21 MB flat tokenizer dir; found beside the checkpoint, so no extra mount

HALOGEN_DOWNLOAD fetches the whole repo into the bind mount on first start only — the entrypoint acts only when the checkpoint is absent, so a restart never re-downloads, and huggingface_hub resumes an interrupted pull. The mount must be read-write for this. Roughly 127 GB; on Dankclaw it lands in /home/dank/models/halogen.

overlay-speed.hgn (2.22 GiB) comes along with the repo but is unused: it trades the o_proj calibration for about 2 % of decode, and the quality sidecar is the default for a reason.

Deployed flags

Everything else is configured by environment variable — there is no config file, and the flags are read once at startup. These are the departures from upstream's defaults:

flag value why
HALOGEN_MODEL_ID frank-large fleet identity; no client rename
HALOGEN_CTX 262144 the model's native context, and what both clients declare
HALOGEN_KV_POOL_POSITIONS 524288 doubled 2026-09-12 to upstream's own default (2 × HALOGEN_CTX): two full-length conversations resident, or four at 131k — 13,312 MiB of KV
HALOGEN_KV_SLOTS 4 four concurrent generations; slots share the pool and cost ~115 MiB each
HALOGEN_MAX_TOK 16384 load-bearing for the doubling, and already at the ceiling. Halves the prefill arena so the pool fits the 29.5 GiB device budget, at ~8–9 % of prefill throughput. At 32768 HALOGEN_KV_POOL_FIT silently reverts the pool to 262144; at 65536 the arena alone exceeds the budget and the server will not boot. See the sizing rule below
HALOGEN_VISION_TOWER 1 image input; the fleet's only image path since frank-npu was retired
HALOGEN_DOWNLOAD peonist-ai/halogen-qwen3.8-flash-next first-start fetch
HALOGEN_VERBOSE 1 verbose engine logging — the fullest startup account, on permanently so an incident report needs no restart-into-debug

Everything else is upstream's default, deliberately: prompt cache mode 2 (two entries per conversation — end-of-system-prompt and end-of-history — which already covers the shared-prefix case), HALOGEN_CACHE_INPLACE=1 (the snapshot stays ~115 MiB at any depth), the speculative drafter 1 (byte-identical at temperature 0, and it stands down whenever a second conversation is generating), the quality sidecar, HALOGEN_ADMIT_CHUNK=0 (a non-zero value gives up the byte-identity property), and the default HALOGEN_MAX_TOKENS_CAP=65536.

Memory model

Three numbers explain the whole box:

  • ~68 GiB pinned weights. The checkpoint is mapped and registered with the GPU in place, never copied. The kernel counts the locked pages as reclaimable file cache, so free, MemAvailable and every dashboard built on them overstate free memory by the size of the model. The server prints the corrected figure at startup; believe that line, not Grafana.
  • ~28 KiB per KV position (measured: 262,144 positions = 6,656 MiB of KV, ~7.2 GiB with block scratch), plus the prefill arena (16.7 GiB at HALOGEN_MAX_TOK=32768, 8.4 GiB at 16384). The engine's device-side budget stops at roughly 47 GiB on a 128 GB machine with the weights pinned — and lower on a machine carrying more besides this server, which Dankclaw is.
  • HALOGEN_HOST_RESERVE_GIB is what is left for the page cache the lookup table is read through. Too little and long prompts crawl with the disk busy and the process in uninterruptible sleep — that is a cache problem, not a memory problem, and the fix is a smaller pool, not a bigger one.

HALOGEN_KV_POOL_FIT=1 (default) measures that budget at startup and lowers the pool itself if the configured one will not fit, printing what it chose. Read those lines on every restart; they are the ground truth for sizing.

Measured ledger, four restarts, read live 2026-09-12. The engine's own startup account:

pool max_tok KV pool arena held host left verdict
262144 32768 7.2 20.6 96.3 12.1 the prior config
524288 16384 14.4 12.2 94.6 13.8 deployed
524288 32768 14.4 20.6 — — pool silently lowered to 262144
524288 65536 — 37.3 — — would not boot — OOM

The sizing rule

One budget covers the pool and the arena together:

device budget = host RAM - resident weights - HALOGEN_HOST_RESERVE_GIB
              = 121      - 67.7             - 24                  = 29.5 GiB

The arena is linear in HALOGEN_MAX_TOK: measured at 3.80 GiB of base plus 8.40 GiB per 16,384 tokens, which predicts all three measured arenas to within 0.1 GiB. The KV costs ~28 KiB a position, so 524,288 of them cost 14.4 GiB. Solving for the arena with the doubled pool in place:

29.5 budget - 1.5 margin - 14.4 pool = 13.6 GiB left for the arena
                                      -> HALOGEN_MAX_TOK <= 19,115

16384 is the largest power of two under that, so the deployed setting is not conservative — it is the ceiling. The corner check confirms it: put max_tok back to 32768 and only 7.4 GiB remains for the pool, about 269k positions, which is precisely the 262,144 config that ran here before. Those two corners are the only points of this box the host has ever served.

Note the consequence for the doubling: it is 1.7 GiB cheaper overall than the config it replaced, because halving the arena gives back more than the extra pool takes.

Two failure modes, and only one is dangerous

Raising max_tok past the ceiling does not shrink the pool — the arena alone outgrows the budget, and the server cannot allocate at all:

kv pool: 524288 positions need ~51.7 GiB ... LOWERING THE POOL TO 262144 (~44.5 GiB).
kv pool: WARNING even 262144 positions (the context, the smallest pool that can
         serve one request) needs ~44.5 GiB and host RAM cannot spare it.
dmalloc: FAILED requesting 0.250 GiB after 39.970 GiB in 566 allocations (out of memory)

This is the quiet one: the unit stays active, the container reports Up (starting), and deploy.sh sits in its health wait for the whole LLM_WAIT rather than failing fast. It confirms upstream's warning that a large HALOGEN_MAX_TOK means "the server will not start", not "it will be slower".

Under-running the ceiling is far more benign and far easier to miss. At 524288 with the arena back at 32768, HALOGEN_KV_POOL_FIT lowered the pool and deploy.sh still reported healthy in 12 seconds:

kv pool: 524288 positions need ~35.0 GiB (plus 1.5 of margin) and host
         RAM cannot spare it. LOWERING THE POOL TO 262144 (~27.8 GiB).

A green health check does not mean the pool you asked for is the pool you got — read the kv pool: lines after every restart.

The 47.7 GiB n-gram lookup table is never held in RAM; it is read through the file cache. The 2.0 GiB the firmware carves for the iGPU appears in no /proc/meminfo figure at all.

Co-tenancy. HALOGEN_FLASH_PIN_TRUNK=1 (default) is what the published decode numbers were measured with, and it means this container holds most of the host. If a co-tenant then takes the remainder, both it and the engine can stall for minutes at a time at full CPU with no disk activity and no output. That is documented behaviour, not a crash, and it needs no restart. HALOGEN_FLASH_PIN_TRUNK=0 gives the memory back and costs several times the decode speed — a last resort, not a tuning option.

Client contract

The differences from llama.cpp that bite are all in the request, not the deployment:

  • No server-side sampler defaults. temperature absent or 0 is greedy decode; above 0 the request samples on the same drafter. Supported fields: temperature, top_p, top_k, min_p, seed, presence_penalty, frequency_penalty, logit_bias, logprobs. Refused with a 400: top_logprobs, logprobs with stream: true, n > 1, and any value outside its defined range (values are refused, never clamped). The fleet runs greedy for clients that stay silent — deterministic, and byte-identical with the drafter.
  • The token budget covers thinking. The default is 8192, and a budget that runs out mid-thought returns finish_reason: "length" with an empty content and the partial reasoning in reasoning_content — which most clients do not display. Above the cap (HALOGEN_MAX_TOKENS_CAP, 65536) a request is a 400 rather than a silent truncation. max_tokens, max_completion_tokens and max_output_tokens all work and must agree if more than one is sent.
  • reasoning_effort is accepted at the top level and inside chat_template_kwargs: minimal, low, medium, high, xhigh. The model's default is xhigh. minimal aliases the template's low and still reasons; enable_thinking: false turns thinking off; preserve_thinking is honoured. preserve_reasoning is a 400 — it is the llama.cpp-era key.
  • /v1/models, /health and completions all report the served id, and reasoning_content carries the reasoning trace.

Pool admission is the one arithmetic trap. A request reserves its prompt plus max_tokens positions when it is admitted; if the pool cannot hold it the request waits in arrival order, and after the queue timeout (3600 s) it gets a 503 engine_busy. A prompt large enough that prompt + budget exceeds the pool can therefore never be admitted at all. With the pool at 524,288 the per-conversation ceiling is HALOGEN_CTX (262,144) — the pool binds how many conversations stay resident, not how long any one of them can be. Under the previous 262,144 pool the two numbers were identical, which is why four concurrent 65k chats were contending for one conversation's worth of positions.

Vision

With the tower loaded, /v1/chat/completions accepts the usual OpenAI image content part carrying a data: URL or bare base64 — http(s) URLs are refused deliberately, because fetching one would make the server issue outbound requests to wherever a client pointed it. One image costs about 2,040 tokens of context and 5.5 / 11.8 / 25.3 s at 1280x800 / 1920x1080 / 2560x1440; text at 12 pt and above is read exactly, and a bigger frame past that point adds empty area rather than detail. Audio and video have no path here at all — that capability left with frank-npu.

Deploy and operate

./scripts/deploy.sh dankclaw --service frank-large

The handler retires the llama.cpp-era root unit first (stops it, drops its enable symlinks, moves /etc/systemd/system/frank-large.service into the home trash — never rm), then pulls ghcr.io/peonist-ai/halogen-flash-server:0.5.8, re-tags it to the localhost/ alias the unit references, installs the Quadlet, and restarts the generated unit. Boot persistence comes from [Install] WantedBy=default.target in the unit file plus linger on the deploy user — generated units cannot be systemctl --user enabled on this host.

The health gate is bootstrap-aware: while the checkpoint is absent the container is downloading and /health cannot answer, so the handler waits for the file instead of burning its budget and reporting a failure that is not one.

systemctl --user status frank-large.service     # the generated unit
podman logs frank-large | head -40              # version banner + memory ledger
curl -s http://127.0.0.1:7770/health            # 200 only after the engine PONGs
curl -s http://127.0.0.1:7770/v1/models

/health asks the engine for a PONG before answering, so a 200 means "ready to serve", not merely "process alive". During the first-start download it stays unhealthy by design.

Troubleshooting

symptom cause
dmalloc: FAILED requesting … (out of memory) then HIP … out of memory the KV pool did not fit. HALOGEN_KV_SLOTS will not fix it (slots share the pool); lower HALOGEN_KV_POOL_POSITIONS to 262144, then HALOGEN_MAX_TOK to 16384 (~9 % prefill)
starts, answers short prompts, collapses to a few tok/s on a long one, disk busy, process in uninterruptible sleep short of file cache, not memory — lower the pool and/or raise HALOGEN_HOST_RESERVE_GIB
long replies that look cut off read finish_reason: stop means you have the whole answer, length means you ran out of budget (thinking counts)
a request that never returns, then 503 engine_busy the pool could not reserve prompt + max_tokens; see the admission trap above
both the engine and a co-tenant stall for minutes at full CPU the pinned-trunk trade; see Memory model
free, MemAvailable, Grafana all wrong by ~68 GiB expected — locked weights are counted as reclaimable

HALOGEN_VERBOSE=1 ships in the unit, so the fullest startup account is already in the log when something goes wrong. HALOGEN_DMALLOC_LOG is deliberately not set: it logs every allocation over 64 MB, which is steady-state noise on a shared host — raise it only for a live OOM report. The lines worth grepping first:

podman logs frank-large 2>&1 | grep -E '^(dmalloc|kv pool):'

Retrieval: podman logs frank-large covers the current instance only — the Quadlet runs --replace --rm, so everything before the last recreate is gone from the container log. journalctl --user -u frank-large.service is the durable record. Both are rootless: sudo podman logs frank-large looks in root's storage and answers "no such container".

Rollback

The llama.cpp era is intact: the STRIX payload stays at /home/dank/models/kingjones-Qwen3.8-Flash-Next-ROCmFP4-STRIX, the kingjones30/ROCmFPX build stays at /home/dank/GitPackages/kingjones-ROCmFPX/build, and the retired unit, env and serve script are in serverAppConfigs/.AGENTTRASH/ (suffixed .llama.cpp). Rolling back is a git revert of this change set plus a deploy — but the Quadlet unit must be removed from ~/.config/containers/systemd/ first (otherwise the restarted root unit and the still-installed container both claim port 7770). See kingjones-strix-rocmfp4.

The amd_iommu=off kernel argument that came with this change is separate and reverts on its own — see dankclaw-iommu-translation-off.

Citations